5 Questions
Which historical concept is related to Deep Learning?
McCulloch Pitts Neuron
What method is used for weight initialization in Deep Learning?
Batch Normalization
Which technique is used for dataset augmentation in Deep Learning?
Autoencoder
Which method is used to address overfitting in auto-encoders?
Sparse auto-encoders
What type of neural network is commonly used in Deep Learning for unsupervised learning tasks?
Multilayer Perceptrons (MLPs)
Study Notes
Historical Concepts and Techniques in Deep Learning
- Connectionism, a historical concept, is related to Deep Learning, which is a subset of Machine Learning that involves neural networks with multiple layers.
Weight Initialization in Deep Learning
- Xavier initialization, a method, is used for weight initialization in Deep Learning to avoid the vanishing or exploding gradient problem.
Dataset Augmentation in Deep Learning
- Data transformation, a technique, is used for dataset augmentation in Deep Learning to artificially increase the diversity of the training dataset.
Overfitting in Auto-encoders
- Regularization, a method, is used to address overfitting in auto-encoders, which are neural networks that learn to copy their inputs.
Unsupervised Learning Tasks in Deep Learning
- Auto-encoder, a type of neural network, is commonly used in Deep Learning for unsupervised learning tasks, which involve training models on unlabeled data.
Test your knowledge of deep learning fundamentals and major algorithms with this quiz based on the course objectives and outcomes from RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL. Challenge yourself to identify the theories, fundamentals, and techniques in deep learning.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
